ANNEX
OUTPUTS VS. OUTCOMES Development results can measure assets, products or services directly delivered by projects (outputs) or the effects that the delivery and use of these assets, prod- ucts or services entail (outcomes). While it is important to know whether outputs have been delivered, development effectiveness assessment typically requires also to know whether the delivered outputs have had the desired effects in improving aspects of people’s lives. Data on outcomes are, however, often more difficult to collect than data on outputs. Most of the results available from OPEC Fund project documentation were data on outputs (such as kilo- meters of road constructed, megawatts installed, schools built, etc.), whereas often their use was not reported, leading to significant data gaps for intermediary outcome indicators such as beneficiaries reached (e.g. students enrolled, patients treated, road users, etc.). COUNTING ACROSS DIFFERENT BENEFIT TYPES As results data does not distinguish the identities of bene- ficiaries, they are counted in each category of develop- ment benefit received. If, for instance, a multisector project targeted rural dwellers with education, health and farming services, reported beneficiaries of these services would be counted separately even if each person benefited from all three. The same applies to the cross-cutting indicator of “women benefited by economic empowerment initia- tives,” wherein, for instance, female farmers who benefited through agricultural economic empowerment initiatives would be counted both as farmers who benefited and as
women benefiting from economic empowerment. The total number of beneficiaries across categories may thus add up to more than the total population in the area of influence.
DATA LIMITATIONS The quality and comprehensiveness of completion reports was variable, posing challenges for the collection of results data. Some examples of data limitations are as follows: • OPEC Fund projects have to date included limited gender-disaggregated data: Only six of 24 MSME loan projects recorded data on women-owned MSME bene- ficiaries (none of the projects reviewed for this year’s edition featured data on women-led MSMEs), and 11 of the 19 projects targeting farmers disaggregated bene- fiting farmers by gender.
• Banking projects this year in many instances do not report the number of MSMEs financed but the volume of loans to these beneficiaries.
• Similarly, the number of jobs supported was not consist- ently documented: Only 21 of all projects recorded jobs data, even though the actual number of projects creating or sustaining employment is assumed to be much higher.
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